And as if you didn't know, today is the last day to vote for Xenomorph in the FTFNews Technology Innovation Awards, so please (pretty please!) take a minute to vote for Xenomorph. You know it makes sense (and big thank you! if you do have time...)

06 March 2015

PRMIA and Bloomberg held a joint event at Bloomberg HQ yesterday evening entitled "How low can yields go?". Tom Keene of Bloomberg News proved himself to be a very dry, amusing and competent moderator and the panel he moderated was comprised of Harley S. Bassman of PIMCO (number of humourous jibes at Harley for having caused the financial crisis due to his involved in credit derivatives), James Sweeney, Chief Economist at CS and Henson Orser of Nomura.

Tom asked the panel the obvious question "How low can yields go?". One response from the panel was that almost every market event was clouded in "deflation hysteria" looking at events such as the recent drop in oil prices. Things will change when this hysteria weakens. Another point made was that current policies (QE) are making safe assets unattractive to release cash into the economy, but that negative interest rates are inherently destabilizing. There was an attitude put forward of "we will survive this" and looking back at the Great Depression then folks pulled money from banks whereas that did not happen in 2008/9. There was some talk of how shorting the bond market 14 months in row has been wrong, but that with 3 1/4% out at 10 years along the US yield curve that this shorting has had no effect on macro policy.

Tom asked whether time "theta" as he put it, was the real healer here. The panel responded that the government's policies of 2009 worked, regardless of your opinion of where the same policies might be taking us long term. A period of balance sheet repair has followed during the 7 years after the crisis and that this was "mostly repaired" looking at many measures of debt. Looking forward, the yield curve is priced for a rate hike and the Fed wants one, but this will not occur until we are nearer full employment at 5-6% and not 8-9% levels. Wage inflation is likely to take off nearer full employment, and growth will start to slow at the same time. There are signs that this is already occurring, and that core inflation in the US is not really that low, only say 30bp less than average.

The panel also discussed the issue that many working on Wall Street had not experienced a tightening economy over the past 10 years so maybe there should be some concerns over how they deal with it through this transition. The panel envisage more FX and rate volatility as this occurs. Against this background, then due to regulation Wall Street had fewer and smaller players to help provide liquidity into this volatile market to come. One of the panelists pointed out issues for equities, with cash flows being discounted at the current (very low) curve whilst returns look weak. One potential scenario build out of this put forward for a rapid increase in inflation over 3-6 months.

Tom asked "How long is history" wanting to establish what timeframe we should be assessing the success of policy. One of the panelists said that baby boomer generation retiring may affect fund flows as they get out of equities and buy bonds and that rates behaviours may have changed for good with markets used to yield curve inversions at around 5/5 1/4% but now moving to 3/3 1/4%. Another panelist mentioned that due to regulation the flow of funds from mortgages and their securitization to sophisticated investors was broken. Again the issue of Wall Street having less capacity due to regulation was mentioned.

On the subject of FX, the panel thought it a very difficult market to forecast. Dollar strength looks set to continue with the possibility of a 85c EUR. The Eurozone may strengthen economically as exports benefit from a weak EUR. Tom asked where investors could capture yield, and Brazil was suggested as a good target given its high rates currently. One of the panelists suggested that the world was taking part in a co-ordinated currency war, but this was not accepted by all. Japan 2015 GDP growth is likely to be good, supported by lower oil prices and experiencing some wage inflation. The Japanese Government cannot buy any more JGBs since the supply is running out, however they think inflation is about to take off there. In summary they thought Abenomics had "worked".

"Stability" and how to recognize it was the next topic from Tom. Firstly the panel thought that whatever is to come in the transition to stability, the world would not unravel. The panel said that stability ex-post was much easier to recognize than ex-ante. One of the panelist put forward a potential scenario in which the Fed could not tighten rates with a very strong dollar, China doing worse/US doing better and therefore everyone wants treasuries.

Audience Q&A - There were a few audience questions. The first was on demographics - asking the panel about the effects on rates and the economy of birth and retirement rates. The panel thought a key issue was whether the cohort of retirees was being replaced by a similar cohort of workers. The US is balanced in this regard but other countries such as Germany, Italy and Japan are not. In the 1980's, Japan did very well economically and had 13 retirees per 100 workers and now this was 48 per 100. However, even for the US then increased longevity of the retiring population was another key issue to address.

Another audience question focused on QE/fiat currencies and whether today's governments where printing more money than the economy has been growing. In summary the panel seemed to think of QE as an experiment that had not gone wrong yet, not to say that it might not and not to say how long it might take to go wrong.

One audience member wondered whether Francis Fukayama's "End of History" now applied to the fixed income and hedge fund industries. The response from the panel was that it is never "different this time" and that greed/ego/hubris had caused problems and would cause problems again. However Wall Street is not dead, and it has the plumbing and machinery to convert granny's savings into funding for an app developer. The last piece of advice from one panel member was to go to the bar and think pleasant thoughts.

24 November 2014

PRMIA put on their Risk Year in Review event at the New York Life Insurance Company on Thursday. Some of the main points from the panel, starting with trade:

The world continues to polarize between "open" and "closed" societies with associated attitudes towards trade and international exposure.

US growth at around 3% is better than the rest of the world but this progress is not seen/benefitting a lot of the poplation yet.

This against an economic background of Japan, Europe and China all struggling to maintain "healthy" growth (if at all).

Looking back at the financial crisis of 2008/9 it was the WTO rules that were in place that kept markets open and prevented isolationist and closed policies from really taking hold - although such populist inward-looking policies are still are major issue and risk for the global economy today.

Aggregate view of risk is still difficult due to siloed systems (hello BCBS239)

Risk aggregation also needs consistency of modelling assumptions, data and analytics all together if you are avoid adding apples and pears

Institutions now need more flexibility in building curves post-crisis with OIS/Libor discounting (see FINCAD white paper)

70% of survey respondents are involved in changes to curve basis

Many new calculations to be considered in collateralization given the move to central clearing

62% of survey respondents are investing in better risk management process, so not just technology but people and process aswell

James was followed by a discussion on market/risk events this year:

Predictions are hard but 50 years ago Isaac Asimov made 10 predictions for 2014 and 8 of which have come true

Bonds and the Dollar are still up but yields are low - this is as a result of relatively poor performance of other currencies and the inward strength of US economy. US is firmly post-crisis economically and markets are anticipating both oil independence and future interest rate movements.

Employment level movements are no longer a predictor of interest rate moves, now more balance of payments

October 15th 40bp movement in yields in 3 hours (7 standard deviation move) - this was more positioning/liquidity risk in the absence of news - and an illustration of how regulation has moved power from banks to hedge funds

Risk On/Off - trading correlation is very difficult - oil price goes means demand up but 30% diver in price over the past 6 months - the correlation has changed

On the movie Interstellar, on one planet an astronaut sees a huge mountain but another sees it is a wave larger than anything seen before - all depends on forming your own view of the same information as to what you perceive or understand as risk

Some points of macro economics:

Modest slow down this quarter

Unemployment to drop to 5.2% in 2015 from 5.8%

CS see the Fed hiking rates in mid-2015 followed by 3 further hikes

The market does not yet agree, seeing a move in Q3 2015

Downside risks are inflation, slow US growth and wages growth anaemic

Upside risks - oil price boost to spending reducing cost of gas from 3.2% down to 2.4% of disposable income

Time for some audience questions/discussions:

One audience member asked the panel for thoughts on the high price of US Treasuries

Quantitative Easing (QE) was (understandably) targetted as having distorting effects

Treasury yields have been a proxy for the risk free rate in the past, but the volatility in this rate due to QE has a profound effect on equity valuations

Replacing maturing bonds with lower yielding instruments is painful

The Fed are concerned to not appear to loose control of interest rates, nor wants to kill the fixed income markets so rate rises will be slow.

One of the panelists said that all this had a human dimension not just markets, citing effectively non-existing interest rate levels but with -ve equity still in Florida, no incentive to save so money heads into stock which is risky, low IR of little benefit to senior citizens etc.

Taper talk last year saw massive sell off of emerging market currencies - one problem in assessing this is to define which economies are emerging markets - but key is that current account deficits/surpluses matter - which the US escapes as the world's reserve currency but emergining markets do not.

Emergining market boom of the past was really a commodities boom, and the US still leads the world's economies and current challenges may expose the limits of authoritarian capitalism

The discussion moved onto central clearing/collateral:

Interest rate assets for collateral purposes are currently expensive

Regulation may exacerbate volatility with unintended consequencies

$4.5T of collateral set aside currently set to rise to $12-13T

Risk is that other sovereign nations will target the production of AAA securities for collateral use that are not AAA

Banks will not be the place for risk, the shadow banking system will

Futures markets may be under collateralized and a source of future risk

One audience member was interested in downside risks for the US and couldn't understand why anyone was pessimistic given the stock market performance and other measures. The panel put forward the following as possible reasons behind a potential slow down:

Income inequality meaning benefits are not throughout the economy

Corporations making more and more money but not proportionate increase in jobs

Wages are flat and senior citizens are struggling

(The financial district is not representative of the rest of the economy in the US however surprising that may be to folks in Manhattan)

The rest of the US does not have jobs that make them think the future is going to get better

Other points:

Banks have badly underperformed the S&P

Regulation is a burden on the US economy that is holding US growth back

Republicans and Democrats need to co-operate much more

House prices need more oversight

Currently $1.2T in student loands and students are not expecting to earn more than their parents

Top 10 oil producers are all pumping full out

The Saudis are refusing to cut production

Venezuela funding policies from oil

Russia desparately generating dollars from oil

Will the US oil bonanza break OPEC - will they be able to co-ordinate effectively given their conflicting interests

Summary - overall good event with a fair amount of economics to sum up the risks for 2014 and on into 2015. Food and wine tolerably good afterwards too!

05 November 2014

The A-Team put on another good event at DMS New York yesterday. Lots of good stuff talked and here are a few takeaways that I remember, after a photo of Ludwig D'Angelo of JPMorgan:

Data Utilities - One of presenters said that "Data Utility" was a really overused term second only to "Big Data". My comment would be that a lot of the managed services folks seem to want to talk about "Data Utilities" - seeming to prefer that term rather than what they are? Maybe because they perceive as better marketing and/or maybe because they hope to be annointed/appointed (how I don't know) as an industry "Data Utility". Anyway for me they fail to address the issue of client-specific data and its management very well, much to the detriment of their argument imho - although SmartStream did say that client data can be mixed up into the data services they offer.

Andrew Gets Literaturally Physical - Andrew Delaney of the A-Team expressed a preference for "physical" books when talking about why the A-Team also prints the Regulatory Data Handbook2 as well as making it available online. I have to agree that holding a book still beats my Kindle experience but maybe I am just getting old. Andrew should check out this YouTube video on how the book was first introduced...

FIBO - The Financial Instrument Business Ontology (FIBO) was discussed in the context of trying to establish industry standards for data. As ever the usage of words like "Ontology" I suspect leaves a lot of business folks looking for the nearest double shot of expresso but that aside, seems like the EDM Council are making some progress on developing this standard. Main point from the event was industry adoption is key. I found some of the comments during the day a bit schizophrenic, in that some said that the regulators should not mandate standards (i.e. leave it to industry adoption and principles) but then in the next breath discussing the benefits (or otherwise) of the LEI (ok, not mandated but specific and coming from the regulators). Certainly the industry needs "help" (is that a strong enough word?) to get standards in place.

Data Quality - Lots on data quality with assessing the business value of data quality initiatives being a key point. On the same subject, Predrag of element-22 announced that the EDM Council will soon be announcing adoption of the Data Quality Index, which could be used to correlate data quality with operational KPIs for the business.

Regulation (doh!) - It wouldn't be a data management event without lots of discussion on regulation - a key point being that even those regulations that are not directly/explicitly about data still imply that data management is key (take CVA calcs for example) - and on a related note it was suggested that BCBS239 should be considered as a more general data managment template for any business objective.

Entity Hierarchies/LEI - Ludwig D'Angelo of JPMorgan gave a great talk and said that vendors were missing a massive opportunity in delivering good hierarchy datasets to clients, and that the effort expended on this at firms was enormous. Ludwig said that the lack of hierarchies in the Legal Entity Identifier (LEI) is a gap that the private sector could and should fill. Ludwig also seemed initially to be thrown when one of the audience suggested that they were multiple "golden copies" of hierarchies needed, since definitions of ownership can differ depending on which department you are in (old battle of risk and finance departments again). Good discussion later of how regulation was driving all systems to be much more entity-centric rather than portfolio-centric, emphasising the importance of getting entity hierarchies right.

DCAM - John Bottega did a great presentation on the Data Management Capability Model (DCAM). John asked Predrag of element-22 to speak about DCAM and he said that unlike previous models (DMM) then this framework would not only assess where you are in data management but will also show you where you need to go. DCAM covers data management strategy / operations / quality / business case / data architecture / tech architecture / governance / program. From what I could see it looked like a great framework - it appeared like common sense and obvious but that is in itself difficult to achieve so good effort I think. Element-22 will offer an online service around DCAM that will also allow anonymous benchmarking of data management capabilities as more institutions get involved (update: the service is called pellustro).

BCBS239 - Big thanks to John M. Fleming of BNY Mellon and Srikant Ganesan of Risk Focus for taking part in the panel with me. Less focus on spreadsheet use and abuse on this panel unlike the London Panel from last month. John had some very practical ideas such as the use of Wikis to publish/gather data dictionary information and with a large legacy infrastructure you are better documenting differences in definitions across systems rather than trying to change the world from day one. Echoing some of the points from DMS London, it was thought that making the use of internal data standards as part of a project sign off was very pragmatic data governance, but that also some systems should be marked/assessed as obsolete/declining and hence blocked from any additional usage in new project work. Bit of a plug for some of our recent work on data validation and exception management, but the panel said that BCBS239 needs to encompass audit/lineage on calculations/derived data/rules in addition to just the raw data

30 October 2014

Great event by Capco and Zicklin Business School at Baruch College in NYC yesterday. Topics went right through from high frequency trading, systemic risk, wealth management and bitcoin. The agenda is here and you can see some on the highlights on twitter at #BankingReloaded.

16 October 2014

A great afternoon event put on by TabbFORUM in New York yesterday with a number of panels and one on one interviews (see agenda). You can see some of went on at the event via the hashtag #TabbTech or via the @XenomorphNews feed.

11 September 2014

A-Team’s DMS Data Management Awards close on the 26th of September so if you haven't already, please vote for Xenomorph!

Xenomorph on the Cloud - First of a few lookbacks at what we have been doing over the past year - firstly with a short animation about one of our major initiatives this year, cloud provision of data management and a new venture into cloud-based data publishing with the TimeScape MarketPlace.

So it would be fantastic if you could support Xenomorph by voting here.

01 July 2014

We had over 60 folks along to our event our the Merchant Taylors' Hall last week in London. Thanks to all who attended, all who helped with the organization of the event and sorry to miss those of you that couldn't come along this time.

Some photos from the event are below starting with Brad Sevenko of Microsoft (Director, Capital Markets Technology Strategy) in the foreground with a few of the speakers doing some last minute adjustments at the front of the room before the guests arrived:

Rupesh Khendry of Microsoft (Head of World-Wide Capital Markets Solutions) started off the presentations at the event, introducing Microsoft's capital markets technology strategy to a packed audience:

After a presentation by Virginie O'Shea of Aite Group on Cloud adoption in capital markets, Antonio Zurlo (below) of Microsoft (Senior Program Manager) gave a quick introduction to the services available through the Microsoft Azure cloud and then moved on to more detail around Microsoft Power BI:

After Antonio, then yours truly (Brian Sentance, CEO, Xenomorph) gave a presentation on what we have been building with Microsoft over the past 18 months, the TimeScape MarketPlace. At this point in the presentation I was giving some introductory background on the challenges of regulatory compliance and the pros and cons between point solutions and having a more general data framework in place:

The event ended with some networking and further discussions. Big thanks to those who came forward to speak with me afterwards, great to get some early feedback.

Come and join Xenomorph, Aite Group and Microsoft for breakfast and hear Virginie O'Shea of the analyst firm Aite Group offering some great insights from financial institutions into their adoption of cloud technology, applying it to address risk management, data management and regulatory reporting challenges.

Microsoft will be showing how their new Power BI can radically change and accelerate the integration of data for business and IT staff alike, regardless of what kind of data it is, what format it is stored in or where it is located.

And Xenomorph will be demonstrating the TimeScape MarketPlace, our new cloud-based data mashup service for publishing and consuming financial markets data and analytics.

In the meantime, please take a look at the event and register if you can come along, it would be great to see you there.

Come and join Xenomorph, Aite Group and Microsoft for breakfast and hear Virginie O'Shea of the analyst firm Aite Group offering some great insights from financial institutions into their adoption of cloud technology, applying it to address risk management, data management and regulatory reporting challenges.

Microsoft will be showing how their new Power BI can radically change and accelerate the integration of data for business and IT staff alike, regardless of what kind of data it is, what format it is stored in or where it is located.

And Xenomorph will be demonstrating the TimeScape MarketPlace, our new cloud-based data mashup service for publishing and consuming financial markets data and analytics.

In the meantime, please take a look at the event and register if you can come along, it would be great to see you there.

14 May 2014

Quick thank you to the clients and partners who took some time out of their working day to attend our breakfast briefing, "Financial Markets Data and Analytics. Everywhere You Need Them." at Microsoft's Times Square offices last Friday morning. Not particularly great weather on here in Manhattan so it was great to see around 60 folks turn up...

Rupesh Khendry of Microsoft (Head of World-Wide Capital Markets Solutions) started the event and set out the agenda for the morning. Rupesh described the expense of data within financial markets, and the difficulties experienced by risk managers in pulling together all the data and analytics they need...

...and following Rupesh was Antonio Zurlo (below) of Microsoft (Senior Program Manager) who explained the fundamentals of Microsoft Azure and what services and infrastructure it offers, including public cloud, virtual private cloud and hybrid cloud architectures. Antonio also described a key usage pattern for HPC/grid on Azure being used to "burst to the cloud" when on-premise infrasture needs to be extended for end/intra-day risk calcs...

Sang Lee (below) of Aite Group (Managing Partner) then delivered his presentation "Floating in the Capital Markets Cloud: Moving Beyond Data Storage". Sang's main findings from the survey of 20 financial institutions were that concerns about security and SLAs relating to cloud usage remain, but even those that were concerned about this also said they were planning to start a cloud project within the next 24 months. Cloud technology seems to becoming more acceptable of late, and Sang said this seems to be due to regulation, cost pressures and the desire to offer better services to clients. Sang confirmed that HPC/Grid with "burst to the cloud" is a common usage pattern and that "Data as a Service" is becoming more popular...

Fred Veasley (below) of Microsoft (Tech Solutions Professional) to introduce Microsoft Power BI and Office 365. Fred explained how Power BI extended the capabilities of Excel with data search (finding and retrieving publicized data sources both within an organization and over the web), its integration capabilities with standard databases, NoSQL databases, data standards such as OData and new APIs/sources of data such as Facebook. Once downloaded, the data can be shaped and merged with other datasets (for instance combining data from positions databases/systems with analytics and data from the cloud), and kept up to date automatically. In addition to Power BI, Power View enables great visualizations and interactive dashboards to be created, and once finalized these can be deployed centrally via web pages down to end users...

After Fred, Brian Sentance (below), CEO of Xenomorph explained the origins of the TimeScape MarketPlace. Based on some discussions with Microsoft about 18 months back, the idea was effectively to firstly to get TimeScape running in the Microsoft Azure cloud, secondly to turn the data management capabilities of TimeScape "upside-down" by using it as a means to upload and publish data to the cloud and thirdly to provide one-to-many access to multiple sources of data via web interfaces and key delivery tools such as Microsoft Power BI. Put another way, without any local software or hardware infrastructure both business users and IT staff can access multiple data sources in the same format and using the same data model wherever the data is needed. In addition to .NET and Java interfaces to the TimeScape MarketPlace via OData, web API delivery into F#, Python, R and MATLAB are all in development...

...and in addition to downloading data via Power BI, Brian also demonstrated how you could build on the data using "Power View" to create powerful analytical dashboard functionality that could be built and tested in Excel, then deployed centrally within a browser for access by users outside of Excel. He added that partners was one of the key aspects for the platform, and introduced the TimeScape MarketPlace Partner Program for the platform to get data, analytics, model vendors, software and service vendors involved and building on the platform. Andrew Tognela (below) of Microsoft (Worldwide Managing Director) closed the presentations...

With 90 registrants so far it looks to be a great event with presentations from Sang Lee of Aite Group on the adoption of cloud technology in financial markets, Microsoft showing the self-service (aka easy!) data integration capabilities of Microsoft Power BI for Excel, and introducing the TimeScape MarketPlace, Xenomorph's new cloud-based data mashup service for publishing and consuming financial markets data and analytics.

30 April 2014

Very pleased to announce general availability of TimeScape Data Validation Dashboard which we announced this morning. You can see find out more here. Big thank you to all the staff and the clients involved, who have helped us to put this together over the past year.

This breakfast briefing includes Sang Lee of the analyst firm Aite Group offering some great insights from financial institutions into their adoption of cloud technology, applying it to address risk management, data management and regulatory reporting challenges.

Microsoft will be showing how their new Power BI can radically change and accelerate the integration of data for business and IT staff alike, regardless of what kind of data it is, what format it is stored in or where it is located.

And Xenomorph will be introducing the TimeScape MarketPlace, our new cloud-based data mashup service for publishing and consuming financial markets data and analytics. More background and updates on MarketPlace in coming weeks.

In the meantime, please take a look at the event and register if you can come along, it would be great to see you there.

31 March 2014

Melissa Sexton of Morgan Stanley introduced the agenda, saying that the evening would focus on three aspects of liquidity risk management:

methodology

industry practice

regulation

LiquidityMetrics by MSCI - Carlo Acerbi of MSCI then took over with his presentation on "LiquidityMetrics". Carlo said that he was pleased to be involved with MSCI (and RiskMetrics, aquired by MSCI) in that it had helped to establish and define standards for risk management that were used across the industry. He said that liquidity risk management was difficult because:

Clarity of Definition - Carlo suggest that if he asked the audience to define liquidity risk he would receive 70 differing definitions. Put another way, he suggested that liquidity risk was "a strange animal with many faces".

Data Availability - Carlo said that there were aspects of the market that we unobservable and hence data was scarce/non-existent and as such this was a limit on the validity of the models that could be applied to liquidity risk.

Carlo went on to clarify that liquidity risk was different depending upon the organization type/context being considered, with banks obviously focusing on funding. He said that LiquidityMetrics was focused on asset liquidity risk, and as such was more applicable to the needs of asset managers and hedge funds given recent regulation such as UCITS/AIFMD/FormPF. The methodology is aimed at bringing traditional equity market impact models out from the trading floor across into risk management and across other asset classes.

Liquidity Surfaces - LiquidityMetrics measures the expected price impact for an order of a given size, and as such has dimensions in:

order size

liquidity time horizon

transaction costs

The representation shown by Carlo was of a "liquidity surface" with x dimension of order size (both bid and ask around 0), y dimension of time horizon for liquidation and z (vertical) dimension of transaction cost. The surface shown had a U-shaped cross section around zero order size, at which the transaction cost was half the bid-ask spread (this link illustrates my attempt at verbal visualization). The U-shape cross section indicates "Market Impact", its shape over time "Market Elasticity" and the limits for what it is observable "Market Depth".

Carlo then moved to consider a portfolio of instruments, and how obligations on an investment fund (a portfolio) can be translated into the estimated transaction costs of meeting this obligations, so as to quantify the hidden costs of redemption in a fund. He mentioned that LiquidityMetrics could be used to quantify the costs of regulations such as UCITS/AIFMD/FormPF. There was some audience questioning about portfolios of foreign assets, such as holding Russian Bonds (maybe currently topical for an audience member maybe?). Carlo said that you would use both the liquidity surfaces for both the bond itself and the FX transaction (and in FX, there is much data available). He was however keen to emphasize that LiquidityMetrics was not intended to be used to predict "regime change" i.e. it is concerned with transaction costs under normal market conditions).

Model Calibration - In terms of model calibration, then Carlo said that the established equity market impact models (see this link for some background for instance) have observable market data to work with. In equity markets, traditionally there was a "lit" central trading venue (i.e. an exchange) with a star network of participants fanning out from it. In OTC markets such as bonds, there is no star network but rather many to many linkages establised between all market participants, where each participant may have a network of connections of different size. As such there has not been enough data around to calibrate traditional market impact models for OTC markets. As a result, Carlo said that MSCI had implemented some simple models with a relatively small number of parameters.

Two characteristics of standard market impact models are:

Permanent Effects - this is where the fair price is impacted by a large order and the order book is dragged along to follow this.

Temporary Effects - this is where the order book is emptied but then liquidity regenerates

Carlo said that the effects were obviously related to the behavioural aspects of market participants. He said that the bright side for bonds (and OTC markets) was given that the trades are private there was no public information, and price movements were often constrained by theoretical pricing, therefore permanent effects could be ignored and the fair price is insenstive to trading (again under "normal" market conditions). Carlo then moved on to talk about some of the research his team was doing looking at the shape of the order book and the time needed to regenerate it. He talked of "Perfectly Elastic" markets that digest orders immediately and "Perfectly Plastic" markets that never regenerate, and how "Relaxation Time" measures in days how long the market takes to regenerate the order book.

Liquidity Observatory - Carlo described how the data was gathered from market participants on a monthly basis using a spreadsheet to categorize the bond/asset class type, and again using simple parameters from active "expert" traders. Take a look at this link and sign up if this is you. (This sounded to me a lot like another "market consensus" data gathering exercise which are proving increasingly popular, such as one the first I had heard of many years back in Totem - we are not quite fully ready for "crowdsourcing" in financial markets maybe, but more people are seeing sense in sharing data.).

Panel Debate - Ron Papenek of MSCI was moderator of the panel, and asked Karen Cassidy of Morgan Stanley about her experiences in liquidity risk management.

Liqudity Risk Management at Banks - Karen started by saying that in liquidity management at Morgan Stanley they look at:

Funding

Operating Capital

Client Behaviour

Since 2008, Karen said that liquidity management had become a lot more rigorous and formalized, being rule based and using a categorisation of assets held from highly liquid to highly illiquid. She said that Morgan Stanley undertake stress testing by market and also by idiosyncratic risk over time frames of 1 month and 1 year. As part of this they are assessing the minimum operating liquidity needed based on working capital needs.

Karen added that Morgan Stanley are expending a lot of effect currently on data collection and modelling given that their data is specific to a retail broker-dealer unit, unlike many other firms. They are also looking at metrics around financial advisors, and how many clients follow the financial advisor when he or she decides to switch firms.

Business or Regulation Driving Liquidity Risk Management - Ron asked Karen what were the drivers of their processes at Morgan Stanley. Karen said that in 2008 the focus was on fundability of assets, saying that the FED was monitoring this on a daily basis. She made the side comment that this monitoring was not unusual since "Regulators live with us anyway". Karen said that it was the responsibility of firms to come up with the controls and best practice needed to manage liquidity risk, and that is what Morgan Stanley do anyway.

Karen added that in her view the industry was over-funding and funding too long in response to regulation, and that funding would be at lower but still pragmatic levels in the absence of regulatory pressure. Like many in the industry, Karen thought the regulation had swung too far in response to the 2008 crisis and would eventually swing back to more normal levels.

Carlo added that he had written an unintentionally prescient academic paper on liquidity management in 2008 just prior to the crisis hitting, and he thought the regulators certainly arrived "after" the crisis rather than anticipating it in any way. He thought that the banks have anticipated the regulators very well with measures such as LCR and SFR already in place.

In contrast, Carlo said that the regulators were lost in dealing with liquidity risk management for asset managers and hedge funds, with regulation such as UCITS being very vague on this topic and regulators themselves seeking guidance from the industry. He recounted a meeting he had with BaFin in 2009 where he told them that certain of their regulations made no sense and he said they acknowledge this and said the asset management industry needed to tell them what to implement (sounds like the German regulator is using the same card as the UK regulators in keeping regulations vague when they are uncertain, waiting for regulated firms to implement them to see what the regulation really becomes...).

What Have We Learnt Since 2008 - Karen said that back in 2008 liquidity was not managed to term, funding basis was not rigorous and relied heavily on unsecured debt. She said that since then Morgan Stanley had been actively involved in shaping the requirements of better liquidity risk management with more rigorous analysis of counterparties and funding capacity. Karen said that stronger governance was a foundation for the creation of better policy and process. She said that regulators were receptive to new ideas and had been working with them closely.

What will be the effect of CCPs on OTC markets? Carlo said that when executing a large order, you have the choice between executing 1) multiple small orders with multiple counterparties or 2) a single large block order with one counterparty. In this regard, the equity and bond markets are very different. In lit equity venues, the best approach is 1), but in the bond markets approach 2) is taken since the trade information is not transparent to the market.

Obviously equity markets have become more fragmented, and this has resulted in improve market quality since it is harder to get all market information and hence the market is less resonant to big events/orders. Carlo added that with the increased transparency proposed for OTC markets with CCPs etc will this improve them? His answer was that this was likely to improve the counterparty risk inherent in the market but due to increased transaparency is likely to have a negative effect on transaction costs (I guess another example of the law of unintended consequencies for the regulators).

Audience Questions - there then followed some audience questions:

LiqidityMetrics extrapolation - one audience member asked about transaction cost extrapolation in Carlo's modelling. Carlo said that MSCI do not extrapolate and the liquidity surface terminates where the market terminates its liquidity. There was some extrapolation used along the time dimension however particularly in relation to the time-relaxation parameter.

LiquidityMetrics "Cross-Impact" - looking at applying LiquidityMetrics to a portfolio, one audience member wondering if an order for one asset distorted the liquidity surface for other potentially related assets. Carlo said this was a very interesting area with little research done so far. He said that this "cross-impact" had not been detected in equity markets but that they were looking at it in other markets such as fixed income where effective two assets might be proxies for duration related trading. Carlo put forward a simple model of where the two assets are analogous to two species of animal feeding from the same source of food.

Long and short position liquidity modelling - one audience member asked Carlo what the effects would be of being long or short and that in a crisis you would prefer to be short (maybe obviously?) given the sell off by those with long positions. Carlo clarified that being "short" was not merely taking the negative number on a liquidity surface for a particular asset but rather a "short" is a borrowing position with an obligation to deliver a security at some defined point, and as such is a different asset with its own liquidity surface.

Changing markets, changing participants - final question of the evening was from one member of the audience who asked if the general move out of fixed income trading by the banks over recent years was visible in Carlo's data? Carlo said that MSCI only have around two years of data so far and as such this was not yet visible but his team are looking for effects like this amongst others. He added that the August 2011 weak banks - weak sovereigns in Europe was visible with signals present in the data.

Good food and good (really good I thought) wine put on by MSCI at the event reception. Great view of Manhattan from the 48th floor of World Trade Centre 7 too.

25 March 2014

I went along to this PRMIA event on Thursday evening hosted by Credit Suisse and sponsored by Acacia Capital. Viktoria Baklanova introduced the panel with Joseph Tenaga as MC for the panel and very quickly got a plug in for her about to be released book written with Joe on money market funds. For those of us who don't know so much about money market funds, then these are a form of interest-bearing fund that invests in short term debt securities. The funds attempt to maintain a stable Net Asset Value (NAV) but to quote Wikipedia they "are widely (though not necessarily accurately) regarded as being as safe as bank deposits yet providing a higher yield." Their role in the 2008 financial crisis echos on strongly through to the present day, with controversy of their supposedly stable NAV (typically $1 in the US) and the associated phrase "Breaking the Buck".

Joe Tenaga started the panel with an (unnecessary in my view) justification of academia, asking the rhetorical question "What is the point of academia?" to which Joe answered that "knowledge is what makes the impossible possible" and he added that knowledge drives us to make things better. Joe introduced the next panelist, Matthew Fink of Oppenheimer Mutual Funds. Matt said that we would be prepared to wager that he had worked in the money market funds area the longest of anyone in the room, having started his involvement in the industry in April of 1971. Matt gave a picture of the mutual funds industry at the time, with around $60B AUM in the US with 95% invested in equities. At that time the mutual funds industry was going through a very bad time, as the economy and markets were falling and fund redemptions were rising to such an extent that they had fallen to $30B over the next few years. At the time, if redemptions had continued at this rate the industry would have vanished.

Against this background for the mutual funds industry, interest rates in the US were very high rising from 6% in 1969 to around 12% in 1974. So many people were paying very high rates on mortgage obligations whilst being limited to receiving only 4-5% on savings due to "Regulation Q". For wealthy individuals, it was possible to get around these savings limits, but only if you had $100,000 to put in a Commercial Deposit or $10,000 into a T-Bill. Ironically it was the regulation to remove one risk (it had been thought that competition on deposit rates had contributed to the bank failures of the Great Depression) that had sparked the drive to innovate to find higher returns and create the money market funds industry as a result, with the first fund being "The Reserve Fund" in 1971. (side comment - if regulation from the 1930's via the 1970 can cause problems in 2014, then I would have to defer to which ever Deity you worsphip to advise on what the longer-term consequencies will be of the current round of complexity being implemented...).

The banks saw the money pouring into money market funds such as those from Fidelity and Dreyfus, and understandably wanted to be part of the party too. Some of the worries about money market funds were firstly what if a fund got into trouble? Secondly, the bank regulators were angry that funds were flowing into this new industry and were concerned that it would increase bank failures. 1979 saw a certain Paul Volcker (ever heard of him?) complaining that money market funds were acting like checking accounts. Matt said that he spoke with Volcker and said that this was not the case, to which Volcker replied that it was true since his wife's company was paying staff wages out on checks written against money market funds.

Henry Shilling of Moody's took over from Matt and showed a few slides, firstly showing the number of funds with AAA (AAAmmf, Aaamf, AAAmf) from Fitch (49), Moody's (130) and S&P Ratings (156). Henry described how regulators have wanted to reduce the risk of funds by shortening the maturity of the debt held from 90 to 60 days, and having one and seven day liquidity windows. He showed that there is a high degree of concentration risk in the industry with the top 10 firms have 74% AUM and the top 20 covering 94% of the AUM for the industry. Similarly, looking at the assets invested in the funds, 80% are from financial institutions.

Igor Axenov of Barclays Capital then showed his slides, illustrating the composition of the funds by asset type prior to the crisis:

ABS related - 34%

Bank products - 23%

Repos - 15%

Corporate - 11%

Unsecured - 8%

Other - 6%

He said that the largest exposure then was to securitized products, with implicit indirect exposure to banks. Igor said that CDO issuance was rising at a rate of $300B per year through 2005/6/7 and that much of the structuring was done to ensure that the ABS products fitted the needs and regulations of money market funds. Detailing the ABS asset composition, Igor showed:

Asset Backed (AB) commercial paper - 50%

AB medium term notes - 24%

Extendible AB commercial paper - 17%

ABS Bonds - 5%

Igor said the asset backed commercial paper market (largely funded through money market funds) had grown to $1.2Trln by 2007, and has fallen precipitously since then down to around $200M now.

Looking at the current money market fund portfolio, it looks like:

Bank products - 41%

Repos - 18%

CP - 15%

US Govt + Agency debt - 10%

Asset backed CP - 9%

Other corporate - 4%

Terence Ma added that the Money Market Fund industry sat at 4Trln in 2008 and was now around $2.7Trln in 2014. Matthew Fink said that given his involvement in regulation that he had "never met the face of the enemy before" in Igor was the start of some lively but well-intended banter between the ex-regulator and structurer.

Terence Ma of South Street Securities described his business, which exclusively involves repurchase agreements "Repos". Terry said that in the 1990's Citi were very disciplined on balanced sheet management and in his opinion, then adhead of the market in this regard. He that the Repo business earns small spreads and as a result needs a big balance sheet. When John Read took over Citi, he decided that he did not like the Repo business since its ROE could not compete with some of the products in retail and other parts of the business. So Terry and his partners wondered whether the Repo business could be managed off balance sheet, so they formed a broker-dealer business and when Citi merged with Salomen Brothers they span off. This was December of 2003 but by 2008 they were left "sucking wind" by the crisis.

Terry was quite explicit that his firm is not part of the "shadow banking system" but are subject to the SEC. He then described a few more things about his business, starting with his definition of a Repo as "an agreement to sell and repurchase a security at a fixed date in the future", with the objectives of providing cash inventory, leverage and short cover. All borrowings are lent out, unlike Lehman Brothers in 2008. They do not finance again structured products unless guaranteed, and only accept collateral from Fannie, Freddie and the US Government.

Joe Tenaga then open out questions to the audience. Someone asked who the first MMF was (I think they missed the first part of the talk) and Matt said that the Keystone MMF filed first but the first was Reserve MMF (which got into trouble in 2008). Matt said that it was interesting that the same people like Paul Volcker were stilled involved with the same concerns about the industry many years on.

The next question was how did early MMFs keep their NAV at $1? Henry said that the "Break the Buck" definition is when there is a mark to market fall of 50bp or more. He said that historically that fund sponsors had addressed any issues with breaking the buck with purchases of the fund at par or direct equity investment in the fund - they did this since the effect on their funds and the industry would be too great to comtemplate. Hence an MMF is not a perfect product but (up until Lehmans in 2008 with a 50% NAV loss) has a near-perfect record. He added that the first funds to break the buck were from Salomon's and First Chicago.

Matt added some further history saying the need to maintain the $1 NAV was initially due to the needs of some of the early investors in the industry, who could not invest in products unless they had fixed NAV. He mentioned that one of the companies, Federated, had a long running battle with the SEC over Money Market Funds, filing for exemptions to avoid some of the restrictions that the SEC was trying to impose since the SEC regarded the MMF industry as damaging the mutual funds industry. He mentioned Rule 2-a7 which defines the accountancy procedures for keeping the NAV at $1, and some of the battles around amortization and penny-rounding policies to facilitate this. To later questions, Matt said that the SEC wants a floating NAV for institutional MMFs but currently wants to leave retail alone (seems somewhat arbitrary choice i.e. lets only change what has been problematic before, ignore anything else and not contemplate what could happen if only we understood things better). He said that the SEC was weak and FSOC is driving the SEC to change (and FSOC itself is a pawn of the Federal Reserve).

Overall an interesting panel, particularly when you have characters such as Matt Fink who know the history and stories within the industry so well.

24 March 2014

The second panel of the day was "Regulation and Risk as Data Management Drivers" - you can find the A-Team's write up here. Some of my thoughts/notes can be found below:

Ian Webster of Axioma responded to a question about whether consistency was the Holy Grail of data management said that there isn't consistent view possible for data used in risk and regulation - there are many regulations with many different requirements and so unnecessary data consistency is "the hobgoblin of little minds" in delaying progress and achieving goals in data management.

James of Lombard Risk suggest that firms should seek competitive advantage from regulatory compliance rather than just compliance alone - seeking the carrot and not just avoiding the stick.

Ian said he thought too many firms dealt with regulatory compliance in a tactical manner and asked if regulation and risk were truly related? He suggested that risk levels might remain unchanged even if regulation demanded a great deal more reporting.

Marcelle von Wendland said she thought that regulation added cost only, and that firms must focus on risk management and margin.

James said that "regulatory risk" was a category of risk all in itself alongside its mainstream comtempories.

Ian added that risk and finance think about risk differently and this didn't help in promoting consistency of ideas in discussions about risk management.

James said that the legacy of systems in financial markets was a hindrince in complying with new regulation and mentioned the example of the relatively young energy industry where STP was much easier to implement.

Laurent of Bloomberg said that young, emerging markets like energy were greenfield and as such easier to implement systems but that they did not have any experience or culture around data governance.

Marcelle said that the G20 initiatives around trade reporting at least promoted some consistency and allowed issues to be identified at last.

Ian said in response that was unconvinced about politically driven regulation, questioning its effectiveness and motivations.

Ian raised the issues of the assumptions behind VaR and said that the current stress tests were overdone.

Marcelle agreed that a single number for VaR or some other measure meant that other useful information has potentially been ignored/thrown away.

General consensus across the panel that fines were not enough and that restricting business activities might be a more effective stick for the regulators.

James reference the risk data aggregation paper from the Basel Committee and suggested that data should be capture once, cleaned once and used many times.

Ian disagreed with James in that he thought clean once, capture once and use many times was not practically possible and this goal was one of the main causes of failure within the data management industry over the past 10 years.

The panel ended with Ian saying that we not just solve for the last crisis, but the underlying causes of crises were similar and mostly around asset price bubbles so in order to recuce risk in the system 1) lets make data more transparent and 2) do what we can to avoid bubbles with better indices and risk measures.

18 March 2014

Rupert Brown of UBS did the keynote at this Spring's A-Team Data Management Summit (DMS). Rupert's talk was about understanding what data there is within a financial institution and understanding where it comes from and where it goes to. Rupert started by asking the question "Where are we?" illustrating it with a map of systems and data flows for an institution - to my recollection I think he said it stretched to 7 metres in length and did not look that accessible or easy to understand. He asked what dimensions it should have as a "map" of data, wondering what dimensions are analogous to latitude, longitude, altitude and orientation? Maybe things like function, product, process, accounting or legal entity as potential candidates.

Briefly Rupert took a bit of a detour into his love of trains with a little history on the London Underground Map. He started by mentioning the role of George Dow who illustrated maps for train routes in a single line, showing just dependency and lineage (what stations are next etc) and ignoring geography and distance. This was built upon by another gentleman, Harry Beck, who took these ideas a stage further with the early ancestors of the current Undergroud map, showing both routes but interweaving all the lines together into a map that additionally was topologically sufficient (indicating broad direction - NESW).

Continuing on with this analogy of Underground to maps of data and data management, Rupert then mentioned Frank Pick who created the Underground brand. Through creating such an identifiable brand, effectively Frank got people to believe and refer to the map, and that people in data governance need and could benefit from taking a similar approach to data governance with data management. I guess it is easy to take maps we see every day for granted and particularly some of the thought that went into them, maybe ideas that initially were not intuitive (or at least not directly representative of physical reality) but that greatly improved understand and comprehension. Put another way, representing reality one for one does not necessarily get you to something that is easy to understand (sounds like a "model" to me).

Rupert then described some of his efforts using Open Street Map to map data, making use of the concepts of nodes, ways and areas. Apparently he had implemented this using a NoSQL database (Mark Logic) for performance reasons (doesn't sound like a really "big data" sized problem with several hundred apps and several thousand data transports but nevertheless he said it was needed, maybe as a result of its graph like nature?). He said that the data was crowdsourced to refine the data, with a wiki for annotations. He said he was interested in the bitemporality of data, i.e. how the map changes over time. He advised that every application should also be thought of as its own "databus" in addition to any de facto databuses might be present in the architecture.

In summary the talk was interesting, but it was demonstrable from what Rupert showed that we have long way to go in representing clearly and easily where data came from, where it goes to and how it is used. I think Rupert acknowledges this and has some academic partnerships trying to develop better ways of representing and visualizing data. Certainly data lineage and audit trail on everything is a hot topic for many of our clients currently, and something that deserves more attention. You can download Rupert's presentation here and the A-Team's take on his talk can be found here.

12 March 2014

Christian Nilsson of S&P CIQ followed up Richard Burtsal's talk with a presentation on data management for risk, containing many interesting questions for those considering data for risk management needs. Christian started his talk by taking a time machine back to 2006, and asking what were the issues then in Enterprise Data Management:

There is no current crisis - we have other priorities (we now know what happened there)

The business case is still too fuzzy (regulation took care of this issue)

Dealing with the politics of implementation (silos are still around, but cost and regulation are weakening politics as a defence?)

Understanding data dependencies (understanding this throughout the value chain, but still not clear today?)

The risk of doing it wrong (there are risk you will do data management wrong given all the external parties and sources involved, but what is the risk of not doing it?)

Christian then moved on to say the current regulatory focus is on clearer roadmaps for financial institutions, citing Basel II/III, Dodd Frank/Volker Rule in the US, challenges in valuation from IASB and IFRS, fund management challenges with UCITS, AIFMD, EMIR, MiFID and MiFIR, and Solvency II in the Insurance industry. He coined the phrase that "Regulation Goes Hollywood" with multiple versions of regulation like UCITS I, II, III, IV, V, VII for example having more versions than a set of Rocky movies.

He then touched upon some of the main motivations behind the BCBS 239 document and said that regulation had three main themes at the moment:

Some further observations were on what will be the implications of the effective "loss" of globablization within financial markets, and also what now can be considered as risk free assets (do such things now exist?). Christian then gave some stats on risk as a driver of data and technology spend with over $20-50B being spent over the next 2-3 years (seems a wide range, nothing like a consensus from analysts I guess!).

The talk then moved on to what role data and data management plays within regulatory compliance, with for example:

LEI - Legal Entity Identifiers play out throughout most regulation, as a means to enable automated processing and as a way to understand and aggregate exposures.

Christian outlined the small budget of the regulators relative to the biggest banks (a topic discussed in previous posts, how society wants stronger, more effective regulation but then isn't prepared to pay for it directly - although I would add we all pay for it indirectly but that is another story, in part illustrated in the document thispost talks about).

In addtion to the well-known term "regulatory arbitrage" dealing with different regulations in different jurisdictions, Christian also mentioned the increasingly used term "subsituted compliance" where a global company tries to optimise which jurisdictions it and its subsidiaries comply within, with the aim of avoiding compliance in more difficult regimes through compliance within others.

I think Christian outlined the "data management dichotomy" within financial markets very well :

Regulation requires data that is complete, accurate and appropriate

Industry standards of data management and data are poorly regulated, and there is weak industry leadership in this area.

(not sure if it was quite at this point, but certainly some of the audience questions were about whether the data vendors themselves should be regulated which was entertaining).

He also outlined the opportunity from regulation in that it could be used as a catalyst for efficiency, STP and cost base reduction.

Obviously "Big Data" (I keep telling myself to drop the quotes, but old habits die hard) is hard to avoid, and Christian mentioned that IBM say that 90% of the world's data has been created in the last 2 years. He described the opportunities of the "3 V's" of Volume, Variety, Velocity and "Dark Data" (exploiting underused data with new technology - "Dark" and "Deep" are getting more and more use of late). No mention directly in his presentation but throughout there was the implied extension of the "3 V's" to "5 V's" with Veracity (aka quality) and Value (aka we could do this, but is it worth it?). Related to the "Value" point Christian brought out the debate about what data do you capture, analyse, store but also what do you deliberately discard which is point worth more consideration that it gets (e.g. one major data vendor I know did not store its real-time tick data and now buys its tick data history from an institution who thought it would be a good idea to store the data long before the data vendor thought of it).

I will close this post taking a couple of summary lists directly from his presentation, the first being the top areas of focus for risk managers:

Counterparty Risk

Integrating risk into the Pre-trade process

Risk Aggregation across the firm

Risk Transparency

Cross Asset Risk Reporting

Cost Management/displacement

The second list outlines the main challenges:

Getting complete view of risk from multiple systems

Lack of front to back integration of systems

Data Mapping

Data availability of history

Lack of Instrument coverage

Inability to source from single vendor

Growing volumes of data

Christian's presentation then put forward a lot of practical ideas about how best to meet these challenges (I particularly liked the risk data warehouse parts, but I am unsurprisingly biassed). In summary if you get the chance then see or take a read of Christian's presentation, I thought it was a very thoughtful document with some interesting ideas and advice put forward.

10 March 2014

Attended a good event at S&P Capital IQ's offices on Tuesday morning last week in London, built around the BCBS 239 document on risk aggregation and reporting (see earlier PRMIA event on this topic too). A partner vendor of S&P CIQ, Tech Mahindra, started the morning with Richard Burtsal's presentation on "Delivering an Enterprise Data Strategy". Tech Mahindra recently acquired a data management platform from UBS Asset Management and are offering a managed service data management offering based on this (see A-Team article).

Richard said that he wasn't going to "sell" in his presentation (always a worrying admission from one of us data management vendors, it usually means entirely the opposite). That small criticism aside, Richard gave a solid update on the state of the industry and obviously on what Tech Mahindra are offering, and added that:

For every $1 spent directly on market data, the total cost of that data goes up by a factor of 6 by the time the data is actually used

33% of rejected trades are caused by incorrect reference data

60% of staff manipulate, report on or support data on a daily basis (I wonder what the other 40% actually do then? Be good to get the Tower Group report this came from to find out maybe?)

25% of reference data management is wasted due to duplication and inefficiences

In their work with UBS Asset Management they had jointly shown that the cost of data management were reduced by 25-30% using a managed service (sounds worth verifying what the "before" situation was I guess, but interesting/impressive).

Clients were pushing for much faster instrument setup and a reduction in time from the 1-2 weeks setup in some systems.

There were a few questions from the audience during Richard's talk, the first asked about the differences in doing data management with the buy-side and data management on the sell-side. Richard said that his experience was that the buy-side managed less instruments (<500,000) but with greater depth of data, and sell-side held more instruments (10M+) but with less depth of data (not sure that completely reflects my experience, but sounds worth a survey maybe).

The second question was why is the utility model for data management going to succeed right now, when previous attempts over the past 10 years had failed? Richard responded that he thought Tech Mahindra would succeed due to:

Tech Mahindra own all their own IP (hmm, not really so sure this is a good reason or even a differentiator, but a I guess aimed at managed services that are not run by the firm that develops the data management system?)

I think the answers to this second question need thinking through more clearly, to be fair Richard had stated the 25% cost reduction already as one benefit, and various folks have said that the technology is ripe for these kinds of offerings now, but all the same the response need to be more fully developed to convince many I think (I remain undecided personally, it would be good to have some more evidence to back this up). One of the S&P CIQ added that what he thinks clients want is "Utility of Delivery" and not "Utility of Content" which I thought was a sensible comment and one that I will be revisiting in the coming months.

On a related note to why managed services just now, another audience member asked how client specific data was managed within a utility or managed service model, and Richard said that client specific data was often managed at the client but that they can upload and integrate client generated data into the managed service offering. I think this is a very key issue within the debate about managed services and utilities, I mean I get the point the data utility proponents make that certain datasets are simple "facts" as such are either write or wrong and hence commoditisable, but much of the data is subjective and all of the data needs validating together in the context of its intended use in my view. I guess I kind of loose myself in looping arguments about why data utility vendors aren't ultimately wanting to be the next Thomson Reuters or Bloomberg (not that that is not a laudible aim but it is not going to change the world or indeed financial markets data provision very much).

03 March 2014

Xenomorph is sponsoring the networking reception at the A-Team DMS event in London this week, and if you are attending then I wanted to extend a cordial invite to you to attend the drinks and networking reception at the end of day at 5:30pm on Thursday.

In preparation for Thursday’s Agenda then the blog links below are a quick reminder of some of the main highlights from last September’s DMS:

I will also be speaking on the 2pm panel “Reporting for the C-Suite: Data Management for Enterprise & Risk Analytics”. So if you like what you have heard during the day, come along to the drinks and firm up your understanding with further discussion with like-minded individuals. Alternatively, if you find your brain is so full by then of enterprise data architecture, managed services, analytics, risk and regulation that you can hardly speak, come along and allow your cerebellum to relax and make sense of it all with your favourite beverage in hand. Either way your you will leave the event more informed then when you went in...well that’s my excuse and I am sticking with it!

11 December 2013

Very pleased that our partnering with Aqumin and their AlphaVision visual landscapes has been announced this week (see press release from Monday). Further background and visuals can be found at the following link and for those of you that like instant gratification please find a sample visual below showing some analysis of the S&P500.

06 December 2013

Quick plug for the New York version of F# in Finance event taking place next Wednesday December 11th, following on from the recent event in London. Don Syme of Microsoft Research will be demonstrating access to market data using F# and TimeScape. Hope to see you there!

27 November 2013

Quick thank you to Don Syme of Microsoft Research for including a demonstration of F# connecting to TimeScape running on the Windows Azure cloud in the F# in Finance event this week in London. F# is functional language that is developing a large following in finance due to its applicability to mathematical problems, the ease of development with F# and its performance. You can find some testimonials on the language here.

Don has implemented a proof-of-concept F# type provider for TimeScape. If that doesn't mean much to you, then a practical example below will help, showing how the financial instrument data in TimeScape is exposed at runtime into the F# programming environment. I guess the key point is just how easy it looks to code with data, since effectively you get guided through what is (and is not!) available as you are coding (sorry if I sound impressed, I spent a reasonable amount of time writing mathematical C code using vi in the mid 90's - so any young uber-geeks reading this, please make allowances as I am getting old(er)...). Example steps are shown below:

The intellisense-like behaviour above is similar to what TimeScape's Query Explorer offers and it is great to see this implemented in an external run-time programming language such as F#. Don additionally made the point that each instrument only displays the data it individually has available, making it easy to understand what data you have to work with. This functionality is based on F#'s ability to make each item uniquely nameable, and to optionally to assign each item (instrument) a unique type, where all the category properties (defined at the category schema level) that are not available for the item are hidden.

The next event for F# in Finance will take place in New York on Wednesday 11th of December 2013 in New York, so hope to see you there. We are currently working on a beta program for this functionality to be available early in the New Year so please get in touch if this is of interest via info@xenomorph.com.

Xenomorph is the leading provider of analytics and data management solutions to the financial markets.
Risk, trading, quant research and IT staff use Xenomorph’s TimeScape analytics and data management solution at investment banks, hedge funds and asset management institutions across the world’s main financial centres.